Progression of a large syphilis outbreak in rural North Carolina through space and time: Application of a Bayesian Maximum Entropy graphical user interface.

In 2001, the primary and secondary syphilis incidence rate in rural Columbus County, North Carolina was the highest in the nation. To understand the development of syphilis outbreaks in rural areas, we developed and used the Bayesian Maximum Entropy Graphical User Interface (BMEGUI) to map syphilis incidence rates from 1999-2004 in seven adjacent counties in North Carolina. Using BMEGUI, incidence rate maps were constructed for two aggregation scales (ZIP code and census tract) with two approaches (Poisson and simple kriging). The BME maps revealed the outbreak was initially localized in Robeson County and possibly connected to more urban endemic cases in adjacent Cumberland County. The outbreak spread to rural Columbus County in a leapfrog pattern with the subsequent development of a visible low incidence spatial corridor linking Roberson County with the rural areas of Columbus County. Though the data are from the early 2000s, they remain pertinent, as the combination of spatial data with the extensive sexual network analyses, particularly in rural areas gives thorough insights which have not been replicated in the past two decades. These observations support an important role for the connection of micropolitan areas with neighboring rural areas in the spread of syphilis. Public health interventions focusing on urban and micropolitan areas may effectively limit syphilis indirectly in nearby rural areas.

Targeted testing for acute HIV infection in North Carolina.

BACKGROUND: Persons with acute HIV infection contribute disproportionately to HIV transmission. The identification of these persons is a critical public health challenge. We developed targeted approaches for detecting HIV RNA in persons with negative serological tests. METHODS: Persons undergoing publicly funded HIV testing in North Carolina between October 2002 and April 2005 were included in this cross-sectional study. We used logistic regression to develop targeted testing approaches. We also assessed simple approaches based on clinic type and geography. Algorithm development used persons with recent HIV infection, determined by a detuned enzyme-linked immunosorbent assay. Validation used persons with acute HIV infection, identified with an HIV RNA pooling procedure. RESULTS: Among 215 528 eligible persons, 232 persons had recent HIV infection and 44 had acute HIV infection. A combination of five indicators (testing site, sexual preference, sex with a person with HIV infection, county HIV incidence, and race) identified 92% of recent infections when testing 50% of the population. In validation among persons with acute HIV infection, this indicator combination had sensitivities of 98% in years 1 and 2 and 88% in year 3. A simple combination of testing site and county performed nearly as well [development (recent infections): sensitivity = 95%; validation (acute infections): sensitivity = 86% in years 1 and 2; 81% in year 3; cut-off established for testing 50% of population.] CONCLUSION: Acute HIV infection can be identified accurately using targeted testing. Simple approaches for identifying the types of clinics and geographical areas where infections are concentrated may be logistically feasible and cost-efficient.

The elimination of anonymous HIV testing: a case study in North Carolina.

In May 1997, anonymous human immunodeficiency virus testing in publicly funded clinics was eliminated throughout North Carolina. There were concerns that this decision would disenfranchise testers with certain behavioral profiles. North Carolina's counseling and testing system was used to evaluate the effect of this policy change. A 10.3 percent decline in overall testing and a 21.7 percent decline among men who had sex with other men were identified in the year following the policy change. However, between 13 and 24 months after the policy change, the number of tests administered returned to near pre-policy levels. Understanding North Carolina's experience can assist others considering similar policy changes.